scholarly journals Comparison of simple and pure shear for an incompressible isotropic hyperelastic material under large deformation

2013 ◽  
Vol 32 (2) ◽  
pp. 240-248 ◽  
Author(s):  
D.C. Moreira ◽  
L.C.S. Nunes
Keyword(s):  
Large Deformation ◽  
Pure Shear ◽  
Hyperelastic Material ◽  
Isotropic Hyperelastic Material

Secondary Biaxial Data Application in a Process of a Hyperelastic Material Characterization

2019 ◽  
Vol 952 ◽  
pp. 275-281
Author(s):  
Rohitha Keerthiwansa ◽  
Jakub Javořík ◽  
Jan Kledrowetz
Keyword(s):  
Material Characterization ◽  
Pure Shear ◽  
Material Model ◽  
Data Fitting ◽  
Hyperelastic Material ◽  
Data Driven ◽  
Data Set ◽  
Frequent Use ◽  
Data Application ◽  
Combined Data

In order to find hyperelastic material model constants, data fitting technique is often used. For this task, the data is collected through different laboratory tests, namely, the uniaxial, the biaxial and the pure shear. However, due to the difficulty in getting biaxial data, often only uniaxial data was used for the fitting. Despite frequent use, it was established that this practice creates erroneous results. With a view to improve the data fitting results and at the same time to overcome the difficulty of collecting primary biaxial data, uniaxial data was used to generate a secondary biaxial data set. The data derived through this method was then tested with four common models as to examine the compatibility of the method. Subsequently, real biaxial data was used to compare with the data fitting results obtained through the proposed method. As results indicated combined data fitting for both instances were very much identical with respect to all tested models. Cases where somewhat higher deviation observed between experimental curves and data fitted curves for biaxial data, gave similar results for adjusted data driven data fitting too. However, such deviation could be attributed to mismatch between models with the particular material behaviour rather than the generated data.

Realizing pure shear mode of dielectric elastomers by tuning biaxial prestress of a deformation controller

2021 ◽  
Author(s):  
Liling Tang ◽  
Yuxi Ding ◽  
Lei Liu ◽  
Junshi Zhang
Keyword(s):  
Large Deformation ◽  
Shear Deformation ◽  
Pure Shear ◽  
Deformation Mode ◽  
Experimental Results ◽  
Free State ◽  
Dielectric Elastomers ◽  
Shear Mode ◽  
Mechanical Loads ◽  
Soft Actuators

Abstract In this article, we propose a method to realize the pure shear deformation mode of dielectric elastomer (DE) membranes by tuning two in-plane prestresses. With utilization of carbon grease electrodes, VHB 4905 membranes are prestretched and attached into a retractable device, forming a pure-shear deformation controller. Experimental results demonstrate that, accurate pure shear deformation mode of DEs can be realized by tuning the mechanical loads in the two directions of the deformation controller. Furthermore, large deformation in the direction of free state can be achieved without electromechanical instabilities. The designed deformation controller accurately realizes the specific pure shear deformation mode of DEs and can be utilized to help design the practical soft actuators.

Hyperelastic Model Selection of Tissue Mimicking Phantom Undergoing Large Deformation and Finite Element Modeling for Elastic and Hyperelastic Material Properties

2011 ◽  
Vol 415-417 ◽  
pp. 2116-2120 ◽  
Author(s):  
Sara Golbad ◽  
Mohammad Haghpanahi
Keyword(s):  
Finite Element ◽  
Large Deformation ◽  
Material Properties ◽  
Soft Tissues ◽  
Nonlinear Behavior ◽  
Strain Energy Function ◽  
Strain Curve ◽  
Breast Cancer Diagnosis ◽  
Hyperelastic Material ◽  
Hyperelastic Model

Pathologies in soft tissues are associated with changes in their elastic properties. Tumor tissues are usually stiffer than the fat tissues and other normal tissues and show the nonlinear behavior in large deformations. There have been a lot of researches about elastography (linear and nonlinear) as a new detecting technique based on mechanical behavior of tissue. In order to formulate the tissue’s nonlinear behavior, a strain energy function is required. For better estimation of nonlinear tissue parameters in elasticity imaging, non linear stress-strain curve of phantom is used. This work presents hyperelastic measurement results of tissue-mimicking phantom undergoing large deformation during uniaxial compression. For phantom samples, 8 hyperelastic models have been used. The results indicate that polynomial model with N=2 is the most accurate in terms of fitting experimental data. To compare the results between elastic and hyperelastic model, a 3-D finite element numerical model developed based on two different materials of elastic and hyperelastic material properties. The comparison confirm the approach of other recent studies about necessity of hyperelastic elastography and state that hyperelastic elastography should be used to formulate a technique for breast cancer diagnosis.

Hyperelastic Material Characterization: A Method of Reducing the Error of Using only Uniaxial Data for Fitting Mooney-Rivlin Curve

2018 ◽  
Vol 919 ◽  
pp. 292-298 ◽  
Author(s):  
Rohitha Keerthiwansa ◽  
Jakub Javořík ◽  
Jan Kledrowetz ◽  
Pavel Nekoksa
Keyword(s):  
Biaxial Tension ◽  
Pure Shear ◽  
Research Work ◽  
Hyperelastic Material ◽  
Primary Data ◽  
Generalized Function ◽  
Data Sets ◽  
Biaxial Test ◽  
Material Constants ◽  
Uniaxial Test

The risk of error in using only uniaxial data for fitting constitutive model curves is emphasized by many hyperelastic material researchers over the years. Unfortunately, despite these indications, often the method is utilized in finding material constants for mathematical models. The reason behind this erroneous practice is the difficulty in obtaining biaxial data. Therefore, as a remedial measure, in this research work we suggest a method of forecasting biaxial data from uniaxial data with a reasonable accuracy. Initially, a set of data is collected through standard uniaxial test. A predefined generalized function is then used to generate a set of values which subsequently used as multiplication factors in order to get biaxial tension data. Eventually, with availability of two data sets, Mooney-Rivlin two parameter model was used for combined data fitting. Material constants were then obtained through least squares approach and thereby theoretical load curves namely uniaxial, equi-biaxial tension and pure shear were drawn. The results of this work suggest a definite improvement related to three curves when compared with only uniaxial test data fitted outcomes. For validation of secondary biaxial data, separate eqi-biaxial test was done and resulting curves were compared. Biaxial primary data curve and forecasted data driven curve show identical data distribution pattern though there is a shift and therefore provide a basis for further research in this direction.

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